In Hawaii, like most U.S. states, households installing rooftop solar photovoltaic (PV) systems receive special pricing under net-metering agreements. These agreements allow households with rooftop solar to buy and sell electricity at the retail rate, effectively using the larger grid to store surplus generation from their panels during sunny times and use it when the sun isn’t shining. If a household generates more electricity than it consumes over the course of a month, it obtains a credit that rolls over for use in future months. Net generation supplied to the grid in excess of that consumed over the course of a full year is forfeited to the utility. Net metering agreements often include a monthly fee to support billing, transmission and operation of the grid.

A growing concern is that the utility has many costs besides the fuel used in electricity generation, and most of these “fixed costs” are lumped in with per- kilowatt hour (kWh) charges. As a result, under current net metering agreements, when a solar customer provides their own power, they don’t pay the fixed- cost component for each kWh they produce. Under a revenue-decoupling rule, those costs are shifted to households and businesses without rooftop solar. As less power is sold in Hawaii, fixed costs per kWh are rising fast. Most of the decrease in power sales is due to gains in efficiency, but some of it is due to installations of solar PV. Residential customers now pay roughly $0.17/kWh for fixed costs. After the drop in oil prices earlier this year, well over half the utility’s revenue from residential customers goes toward fixed costs.

The graph shows the average residential electricity price from 2000 to the present, and breaks out the generation component from the total (Adjusted ECAF). The difference between price and the Adjusted ECAF (Gap) accounts for all non-fuel or fixed costs.

A longer-term concern, particularly in Hawaii with its high electricity rates, is that an inefficient pricing system could encourage many households and businesses to install stand-alone systems, unplug from the grid, and further raise costs for everyone else.

In a new report UHERO's Energy Policy & Planning Group summarizes the benefits and challenges with distributed solar and sketch out a set of long-term solutions based on marginal-cost pricing as the primary platform. Marginal cost is the incremental cost of power production—the cost of generating one more kWh. This cost can vary a lot depending on total demand and the amount of renewable power, among other things, so ideal prices would vary over the course of each day, week, season and year. This is likely to become especially pronounced as the variable supply from renewable sources becomes more prominent.

Kīlauea volcano is the largest stationary source of sulfur dioxide (SO₂) pollution in the United States of America. The SO₂ that the volcano emits eventually forms particulate matter, another major pollutant. In a recent project, we use this exogenous source of pollution variation to estimate the impact of particulate matter and SO₂ on emergency room admissions and costs in the state of Hawai‘i.

To accomplish this, we employ two sources of data. The first is measurements of air quality collected by the Hawai‘i Department of Health taken from various monitoring stations across the state. The second is data on emergency room utilization due to cardio-pulmonary reasons which we obtained from the Hawai‘i Health Information Corporation. An important feature of our study is that our cost data are more accurate than the cost measures used in much of the literature. We then merged these data by region and day to obtain a comprehensive database of air quality and medical care utilization in the State of Hawai‘i. Importantly, we employed coarse geographic information on the patients’ residence (as opposed to the hospital in which they were admitted) when computing the utilization time series by region to ensure that our utilization measures corresponded more accurately with the pollution exposure. Using the merged database, we then employed regression techniques in which we related ER utilization and charges to measures of exposure to particulates and SO2 while controlling for comprehensive seasonal patterns and regional effects.

We find strong evidence that particulate pollution increases pulmonary-related hospitalization. Specifically, a one standard deviation increase in particulate pollution leads to a 2-3% increase in expenditures on emergency room visits for pulmonary-related outcomes. However, we do not find strong effects for pure SO₂ pollution or for cardiovascular outcomes. We also find no effect of volcanic pollution on fractures, our placebo outcome. Finally, the effects of particulate pollution on pulmonary-related admissions are most concentrated among the very young. Our estimates suggest that, since the large increase in emissions that began in 2008, the volcano has increased healthcare costs in Hawai‘i by approximately $6,277,204.

These estimates provide evidence of some of the external costs of particulate pollution. Importantly, other studies have had a difficult time unraveling the effects of particulate pollution from other types of pollution such as carbon monoxide because they tend to be highly correlated. In contrast, in our data, the correlation between particulate pollution and other pollutants (aside from SO2, of course) is considerably smaller than the other literature on the topic that largely relies on manmade sources of pollution. In this sense, we provide one of the best available estimates of the pure impact of particulate pollution on human health.

Changes in population age structure have important implications for the economies of all countries irrespective of their level of development. One reason age structure is so important is that children consume but produce little or nothing through their own labor. To survive and prosper they must depend on transfers from adults – their parents, of course, but also tax payers. High material standards of living are harder to achieve in countries with young populations, because the number of productive adults is low relative to the number of dependent children. Fertility decline has led to a demographic dividend as the number of dependent children has declined relative to the number of working-age adults. This phenomenon is captured by trends in the support ratio, a key summary measure shown in the Interactive Data Explorer. Other things equal, output per consumer is proportional to the support ratio, and the rate of growth of output per consumer equals the rate of growth of the support ratio.

The Interactive Data Explorer is based on National Transfer Accounts (NTA) and population estimates and projections for forty countries that vary greatly in their level of development, social, political and economic systems, and demographics. The interactive tool can be used to explore the economic role of age structure since 1950 and to assess the likely influence of demography over coming decades. The support ratio is a useful summary measure, but it is also important to drill more deeply into the data, a task made easier by the data explorer.

The rise in the support ratio or what we call the “first demographic dividend” can be seen by tracing the past of most high-income countries and many developing countries that now have low levels of fertility. South Korea’s support ratio, for example, increased from 0.67 in 1973 to 0.95 in 2006, a gain of over 30 percent. In some countries, like China and Vietnam, the gains are even greater. The Interactive Data Explorer shows that in other countries the first demographic dividend is more modest and that many African countries are just beginning to experience it.

An important question: Why does the support ratio rise more in some countries than others? One of the most important factors is the speed of fertility decline. The importance of this factor can be judged using the Interactive Data Explorer by selecting a country and a year in the future and then by choosing among alternative fertility scenarios. For Ethiopia in 2060, for example, the projected support ratio is 0.90 for the “Medium” fertility scenario as compared with 0.71 if fertility remains constant at the current level.

The economic impact of changing age structure depends on features of the economic lifecycle as measured by per capita consumption and labor income by age in National Transfer Accounts. On average, the gap between consumption and labor income is less for children and older adults in lower income countries than in higher income countries. In higher income countries, spending on the costly education of each child is relatively high, and often consumption by the elderly is much higher than consumption by younger adults. This can be seen by setting the Preview to “Per Capita Profiles” and looking at the thumbnails for 40 countries. (Spending on education, health, and other components of consumption is available in NTA but not shown in the data explorer.) General patterns can be seen in the per capita profiles, but also the importance of country-specific features. In a number of African countries the gap between consumption and labor income is high even among those in their 20s. This results in a depressed support ratio.

The rise in the support ratio is a transitory phenomenon and as populations begin to age the support ratio inevitably drops to lower levels. To see why this happens, pick a country, set Scale to “Percentages”, and press “play”, watching the upper right figure titled “Aggregate Consumption and Labor Income by Age”. Instead of high consumption among children, we have high consumption among the elderly. The transition is particularly strong in rapidly aging societies in East Asia and parts of Europe.

Fertility also plays a role here and given the low fertility scenario, aggregate consumption by the elderly would reach very high levels in many countries at time goes on. This can be seen by choosing some future year such as 2050 and varying the fertility level. The rise in old age consumption has a silver lining, however, to the extent that the elderly fund their own consumption by accumulating wealth or capital during their working years. Under these circumstances, the growth in old-age consumption will lead to a second demographic dividend as higher capital fuels development in the host country and possibly in other countries through higher rates of foreign investment.

The economic rebound from the bottom of the Great Recession was less vigorous than post-recession rallies of the past. Notwithstanding some recent pickup of momentum in the US, output growth in developed countries has continued to remain relatively subdued. But should we expect to see any faster growth going forward? Two prominent economists, John Fernald* and Robert Gordon**, point to demographic changes and declining productivity as the limiting factors behind the economy’s lower growth potential.

Most rich countries are facing a handicap due to their stagnant and aging populations. With the ongoing retirement of baby-boomers, the declining labor-force participation rate creates a drag on potential growth. Some of these headwinds have been counterbalanced by growing employment, but faster economic growth would require an unlikely acceleration of labor market improvement. In other words, labor force participation would have to strengthen, or the unemployment rate, which has been falling roughly one percent per year in the US, would have to decline even faster, from 5.6% in December, 2014 to 3.0 percent or below by 2017!

Annual productivity growth, another component of economic expansions, has averaged 0.5% since the recovery started and 1.2% over the past decade in the US. These values are far below the temporary, informationtechnology- fueled pace seen in the mid-1990s and early 2000s. An increase in productivity growth requires an increase in the pace of innovation. So once the main breakthroughs of the IT revolution were fully incorporated into creative processes, they stopped stimulating a further surge in productivity. There were other drivers of exceptional growth earlier in the twentieth century, including electrification, the introduction of the internal combustion engine, and the construction of the Interstate Highway System, but since the 1970s the internet boom was the only episode that elevated productivity growth above 2%.

Slower economic growth has direct consequences for our quality of life. It reduces the chance that today’s generation of young people will double their parents’ standard of living, as has historically occurred across generations. It also increases the burden of public debt by reducing future tax revenues and the size of the economy that finances the debt. The limiting factors mentioned above also have implications for monetary policy. Despite its lackluster growth, the economy may actually be expanding faster than its potential growth rate at present, eventually resulting in upward pressure on wages and the inflation rate and potentially prompting the Fed to raise interest rates sooner rather than later. Finally, slow growth is likely to affect the demand side of the economy in the form of shrinking disposable income and reduced investment.

Demand side proposals to stimulate the economy emphasize the importance of public and private investment. With unfavorable demographic prospects and nominal interest rates close to zero, policy makers also need to fight deflationary expectations. As a response, central banks could raise their inflation targets to 4%, and thereby potentially push real interest rates lower. Supply side policy options for accelerating growth include reforms of the education system, the labour market, and the social welfare system. However, each of these proposals is likely to face political opposition.

Developing countries will feel the effects of reduced demand from rich countries, but many have relatively young populations and rising educational attainment that makes them less vulnerable to the looming growth challenges of the developed world. As a result, future drivers of growth might include India, Latin America, and even Africa. If relatively more global resources flow toward these countries, they may be able to narrow the development gap with the world’s richest countries.

As of January 12, the Brent Crude Price was just a shade under $47 per barrel. The last time prices were this low was nearly 5 years ago, in April, 2009. Since crude oil and its products feed into about 90% 70% of electricity generated in Hawai’i, it is almost axiomatic to expect electricity prices to decline with oil prices.

But it takes some time for oil prices to feed into electricity prices. The price Hawaiian Electric Industries pays for oil in any month is closely connected to the average Brent crude price in the three previous months (figure 1). So, if prices stay this low, it will take up to four months before electricity prices fully reflect the drop in oil prices.

The relationship between the lagged average oil price and electricity price implies that each dollar per barrel decline in oil price should lead to a 0.22 cents/kWh decline in electricity price (figure 2). We use this relationship to project electricity prices under two assumptions about the future price of oil: (i) oil prices remain constant at the January 12 level, or (ii) oil prices follow the path predicted by the January 12 futures prices for Brent crude. (Futures prices are prices that can be locked in today for delivery up to 5 years from now).

Figure 3 shows these projections. Assuming oil prices stay at current prices, electricity prices should decline to around 18 cents/kWh by the middle of the year, and stay there. As of January 12, futures prices are above spot prices, so the second scenario has electricity prices falling to 18 cents/kWh but then gradually increasing to 23 cents/kwh thereafter.

Either way, the savings will be substantial. For a household consuming 600kWh, the 10 to 15 cent/kWh decline translates into $60 to $90 off their monthly bill. Since Hawai`i is consuming 790GWh on average, the almost $60 decline in oil prices should save the State’s economy about $104 million every month, with about three quarters of that amount going to businesses and municipalities and a quarter of it going to households.

With Hawai’i being the most oil-dependent state in the country, plus that fact that we import all of our oil, our state may benefit more than any other from the precipitous decline in oil prices.